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applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata. Build and evaluate monocular depth pipelines
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None Additional Preferred Experience working in one or more of the following areas: Longitudinal data analysis Predictive modeling/machine learning models Biostatistics / epidemiological modeling
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conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in-distributed-wireless-systems/ Distributed MIMO
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 8 days ago
differential equations # Knowledge of Scientific computing / high-performance computing # Knowledge of Algorithmic modeling and simulation # Fundamentals of machine learning or quantum computing # Programming
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research will be conducted within the VLAIO ICON NEXT-WIND project, which aims to develop next-generation forecasting methods combining machine learning weather prediction models with renewable energy
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Hospital, Copenhagen). The successful candidate will be responsible for designing and implementing the predictive modeling strategy of the project. This includes: Developing machine-learning prediction
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will apply machine learning — in particular physics-constrained symbolic regression — to discover compact analytical spin-Hamiltonians and their parameter dependencies. These Hamiltonians will feed large
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Biology Scientist in Single-cell omics & AI to support the valorization trajectory of a computational platform combining single‑cell omics, AI machine learning, and translational biology. The role involves
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from various sources, and collating them into datasets suitable for the training and evaluation of predictive models Training and evaluating predictive machine learning models on historical data from
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accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large